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1
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| 授業計画/Class |
概論【オンライン（オンデマンド型）】:
人工知能の概要，歴史，定義の多様性
Introduction:
an overview, brief history and various definitions of artificial intelligence (AI) |
| 事前学習/Preparation |
シラバスを読んで，人工知能のキーワードを確認する．
Read the syllabus of this course and investigate keywords of AI. |
| 事後学習/Reviewing |
教材を復習する．
Review the teaching materials.
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2
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| 授業計画/Class |
探索法 (1):【オンライン（リアルタイム型）】
系統的探索法（幅優先探索と深さ優先探索）
Search Algorithms (1):
systematic search (breadth-first search and depth-first search)
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| 事前学習/Preparation |
教材と参考書を読む．
Read the teaching materials and reference books. |
| 事後学習/Reviewing |
宿題と教材の復習．
Exercises and review the teaching materials. |
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3
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| 授業計画/Class |
探索法 (2):
発見的探索法（山登り法とA*アルゴリズム）
Search Algorithms (2):
heuristic search (hill-climbing and A* algorithm)
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| 事前学習/Preparation |
教材と参考書を読む．
Read the teaching materials and reference books.
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| 事後学習/Reviewing |
宿題と教材の復習．
Exercises and review the teaching materials. |
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4
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| 授業計画/Class |
問題分解法とゲーム木探索：
AND/ORグラフ，ミニマックス法，アルファベータ法
Game Tree Search Algorithms:
and-or graph, minimax, alpha-beta pruning
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| 事前学習/Preparation |
教材と参考書を読む．
Read the teaching materials and reference books.
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| 事後学習/Reviewing |
宿題と教材の復習．
Exercises and review the teaching materials. |
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5
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| 授業計画/Class |
記号論理：
命題論理と述語論理
Symbolic Logic:
propositional logic and predicate logic
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| 事前学習/Preparation |
教材と参考書を読む．
Read the teaching materials and reference books. |
| 事後学習/Reviewing |
宿題と教材の復習．
Exercises and review the teaching materials. |
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6
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| 授業計画/Class |
論理プログラミング：
ファクト，変数，ルール，リスト
Programming in Logic:
Facts, Variables, Rules, Lists
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| 事前学習/Preparation |
教材と参考書を読む．
Read the teaching materials and reference books.
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| 事後学習/Reviewing |
宿題と教材の復習．
Exercises and review the teaching materials. |
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7
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| 授業計画/Class |
プロダクションシステム (1)：
ワーキングメモリ 知識ベース，推論エンジン，前向き推論，後ろ向き推論，競合解消戦略
Production System (1):
working memory, knowledge base, inference engine, forward reasoning, backward reasoning, conflict resolution strategy
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| 事前学習/Preparation |
教材と参考書を読む．
Read the teaching materials and reference books.
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| 事後学習/Reviewing |
宿題と教材の復習．
Exercises and review the teaching materials. |
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8
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| 授業計画/Class |
プロダクションシステム (2)：
プロダクションルール構築演習
Production System (2):
Exercise of constructing production rules
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| 事前学習/Preparation |
教材と参考書を読む．
Read the teaching materials and reference books.
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| 事後学習/Reviewing |
宿題と教材の復習．
Exercises and review the teaching materials. |
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9
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| 授業計画/Class |
知識表現：
意味ネットワーク，フレーム，オントロジー
Knowledge Representations:
semantic networks, frames, ontologies
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| 事前学習/Preparation |
教材と参考書を読む．
Read the teaching materials and reference books. |
| 事後学習/Reviewing |
宿題と教材の復習．
Exercises and review the teaching materials. |
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10
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| 授業計画/Class |
機械学習 (1)：
機械学習の概要，教師あり学習
Machine Learning (1):
overview of machine learning and supervised learning
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| 事前学習/Preparation |
教材と参考書を読む．
Read the teaching materials and reference books.
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| 事後学習/Reviewing |
宿題と教材の復習．
Exercises and review the teaching materials. |
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11
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| 授業計画/Class |
機械学習 (2):
教師なし機械学習（クラスタリング）
Machine Learning (2):
unsupervised learning (clustering)
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| 事前学習/Preparation |
教材と参考書を読む．
Read the teaching materials and reference books.
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| 事後学習/Reviewing |
宿題と教材の復習．
Exercises and review the teaching materials. |
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12
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| 授業計画/Class |
機械学習 (3):
教師なし機械学習（相関ルールマイニング）
Machine Learning (3):
unsupervised learning (association rule mining)
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| 事前学習/Preparation |
教材と参考書を読む．
Read the teaching materials and reference books.
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| 事後学習/Reviewing |
宿題と教材の復習．
Exercises and review the teaching materials. |
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13
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| 授業計画/Class |
人工ニューラルネットワーク：
パーセプトロン，多層パーセプトロン，勾配降下法，誤差逆伝播法
Artificial Neural Networks:
perceptron, multilayer perceptron, gradient decent methods, backpropagation
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| 事前学習/Preparation |
教材と参考書を読む．
Read the teaching materials and reference books.
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| 事後学習/Reviewing |
宿題と教材の復習．
Exercises and review the teaching materials. |
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14
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| 授業計画/Class |
深層学習：
深層学習の歴史，分類，課題，応用
Deep Learning:
a brief history, types, issues and applications of deep learning
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| 事前学習/Preparation |
教材と参考書を読む．
Read the teaching materials and reference books.
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| 事後学習/Reviewing |
宿題と教材の復習．
Exercises and review the teaching materials. |
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15
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| 授業計画/Class |
人工知能の応用:
質問応答システム，音声対話システム，統合知能アプリケーション
Applications of AI:
question answering systems, spoken dialogue systems, integrated intelligence applications
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| 事前学習/Preparation |
教材と参考書を読む．
Read the teaching materials and reference books.
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| 事後学習/Reviewing |
教材を復習する．
Review the teaching materials.
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